Central American Crop Vegetation and Precipitation Indices

Four distinct vegetation indices—ARVI, NDVI, EVI, and SIPI—are combined with five Standardized Precipitation Index (SPI) timeframes to monitor agricultural and environmental conditions. The dataset is organized by country, department, municipality, year, and month, providing monthly average values. It was produced and transformed by GIS4Tech for the PREDISAN platform and last updated in April 2026.

Use Cases

• Correlate the Enhanced Vegetation Index (EVI) with the 3-month Standardized Precipitation Index (SPI3) to assess short-term drought impacts on crop health.
• Analyze the Normalized Difference Vegetation Index (NDVI) trends by municipality and year to identify long-term changes in vegetation activity.
• Use the Atmospherically Resistant Vegetation Index (ARVI) and Structure Insensitive Pigment Index (SIPI) to differentiate crop types and monitor pigment variations across departments.
• Model the relationship between the 12-month Standardized Precipitation Index (SPI12) and annual vegetation index averages to study medium-term hydrological stress on ecosystems.
• Compare SPI1 (immediate impact) and SPI9 (medium-term) values against vegetation indices to build early warning systems for agricultural drought.

Strengths

• Integrates four specialized vegetation indices (ARVI, NDVI, EVI, SIPI) derived from remote sensing.
• Includes five standardized precipitation indices (SPI1 to SPI12) for different impact timeframes.
• Data is categorized at multiple administrative levels: country, department, and municipality.

Limitations

• The exact number of records, geographic resolution (e.g., pixel size), and temporal range are not specified.
• Data represents monthly averages, which may obscure shorter-term events critical for immediate impact analysis.
• Potential reliance on satellite data introduces limitations related to cloud cover and sensor calibration.

Provenance

Source

Acción contra el hambre - GIS4tech, via the PREDISAN platform.

Collection Method

Indices calculated from remote sensing data (e.g., satellite imagery) and transformed by GIS4Tech.

Freshness

Last updated in April 2026, indicating planned maintenance.

Geography

Central America, with data categorized by country, department, and municipality.